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CNNRes-DIndRNN: A New Method for Detecting TLS-Encrypted Malicious Traffic

While ensuring the accuracy of encrypted malicious traffic detection, improving model training speed remains a challenge. In order to solve this challenge, we propose CNNRes-DIndRNN for detecting encrypted malicious traffic classification. This model uses 1D-CNN to capture local feature relationship...

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Principais autores: Jinsha Zhang, Xiaoying Wang, Chunhui Li, Qingjie Zhang, Guoqing Yang, Xinyu Li, Fangfang Cui, Ruize Gu, Panpan Qi, Shuai Liu
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2025-12-01
coleção:Future Internet
Assuntos:
encrypted malicious traffic classification
convolutional neural networks
recurrent neural networks
time-series algorithm
SSL/TLS
Acesso em linha:https://www.mdpi.com/1999-5903/18/1/8
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